Milk is the only known substance in nature that can provide the body with complete and balanced nutrition. Recombined milk is a milk replacement product. Recombined milk components are more easily adjustable than milk components. Using electrical conductivity, valuable information is available about the quality of different materials, including food. In addition, by this method, as a simple and practical tool, the quality of many foods can be controlled. In this study, Response Surface Methodology (RSM) was used for modeling and optimization of the electrical conductivity of recombined milk. The effects of protein (1, 2, 3, 4 and 5%), Lactose (4, 6, 8, 10 and 12%), fat (3 and 6%) and temperature (50, 55, 60, 65 and 70º, C) independent variables on electrical conductivity of recombined milk as dependent variables (response) were evaluated. Process variables were statistically significant (p<0. 01) as quadratic regression model for this response. The R2 factor for the modeling of the electrical conductivity of Recombined milk was 0. 92 by the response surface method. Optimum conditions for the electrical conductivity of the Recombined milk in the usual range (4 to 5. 5 mS/cm) contained protein 3. 4%, lactose 7. 7%, fat 3% and temperature of 63. 9 °, C.

In this study, the electrical conductivity of recombined milk was modeled and predicted using artificial neural networks (ANN) method. The protein (1, 2, 3 and 4%), lactose (4, 6, 8 and 10%), fat (3 and 6%) and temperature (50, 55, 60 and 65º C) were considered as the independent input parameters and electrical conductivity of recombined milk as the dependent parameter. Experimental data obtained from electrical conductivity meter, were used for training and testing the network. In order to develop neural network firstly experimental data were randomly divided into three sets of training (70%), validating (15%) and testing model (15%). In order to develop ANN models. Multilayer perceptron networks (MLP) models were trained in two, three and four layers. The number of hidden layers and the number of neurons in each layer were obtained by trial and error. The best training algorithm was LM with the least MSE value. The highest coefficient of determination (R2) and lowest mean squared error (MSE) were considered as the criterion for selecting the best network. The network having three layers with a topology of 4-4-1 had the best results in predicting the electrical conductivity of recombined milk. This network has four neurons in the hidden layer. For this network, R2 and MSE were 0. 992 and 0. 011, respectively. These results can be used in milk processing factories. The correlation between the predicted and experimental values in the optimal topologies was higher than 99%.

Introduction: Among the foods consumed on a daily basis, milk has the most appropriate and balanced ingredients, that is the reason milk called whole food. Milk is the only known substance in nature that can provide human body with complete and balanced nutrition. Recombined milk is a milk replacement product. Recombined milk components are more easily adjustable than milk components. The electrical conductivity is referred to as conductivity of a specific material against electric current, which is expressed in micro Siemens units per cm (mS/cm). Using electrical conductivity, valuable information is available about the quality of different materials, including food. In addition, by this method, as a simple and practical tool, the quality of many foods can be controlled. The aim of this study was to investigate the electrical conductivity of recombined milk affected by temperature, protein percentage and lactose content. Materials and methods: In order to investigate the effect of protein percentage (1, 2 and 3%) and percentage of lactose or sugar content (4, 6 and 8%) on the electrical conductivity of milk, pure dry milk powder without dietary supplementation was used. Lactose powder was used to increase the lactose content of dry milk powder. Sodium caseinate was used to increase the protein content of dry milk powder. Distilled water was used to increase the volume of samples. Total experiments were carried out at three temperature levels (50, 55 and 60 º C). Data analysis was also done using SPSS 16 software. Results and discussion: The results showed that temperature, protein percentage and lactose percentage had a significant effect on the electrical conductivity of recombined milk. The electrical conductivity of the recombined milk ranged from 2. 31 to 5. 7 mS/cm at 50° C, 8% lactose, 1% protein and 60° C, 4% lactose, 3% protein, respectively. The greatest and least effect on the electrical conductivity of recombined milk was related to the effect of protein percentage and lactose percentage, respectively. By increasing the temperature, the electrical conductivity of the reconstituted milk has increased significantly. The greatest changes in electrical conductivity (16%) of recombined milk occurred by the influence of temperature factor in protein 1% and lactose 4% and its value ranged from 2. 44 to 2. 83 mS/cm. In addition, the lowest changes in electrical conductivity (6%) of recombined milk were obtained by the temperature factor of 3% protein and 8% lactose, and it was increased from 4. 68 to 4. 95 mS/cm. By increasing protein content, the electrical conductivity of recombined milk has increased significantly. The most changes in electrical conductivity (107%) of recombined milk occurred by the influence of protein percentage at 55 ° C and 6% lactose, and its value ranged from 2. 42 to 5. 6 mS/cm. In addition, the lowest changes in the electrical conductivity (100%) of reconstituted milk occurred by the influence of protein percentage at 55 ° C and 4% lactose, and its content increased from 2. 5 to 5 mS/cm 5. These results indicate that protein percentage factor has the most effect on the electrical conductivity of recombined milk (compared to two temperature factors and lactose percentage). By increasing lactose content, the electrical conductivity of recombined milk has decreased significantly. The greatest changes in electrical conductivity (13%) of recombined milk occurred by the influence of lactose percentage at 60 ° C and protein 3%, and its content decreased from 5. 7 to 4. 95 mS/cm. Also, the smallest changes in electrical conductivity (1. 5%) of reconstituted milk occurred by the influence of lactose percentage at 55 ° C and 2% protein, and its content decreased from 5. 55 to 4. 48 mS/cm. The maximum and minimum amount of electrical conductivity of reconstituted milk was 5. 7 mS/cm at 60° C, 4% lactose and 3% protein, and 2. 31 mS/cm at 50° C, 8% lactose and 1% protein, respectively.

Milk thistle (Silybum marianum (L.) Gaertn) belonging to the Asteraceae family and known for its valuable secondary metabolite, silymarin. In order to get the cell suspension culture of Silybum marianum, the combination of 2,4-D and BAP hormones each with five different concentrations (0, 0.1, 1, 2 and 5 mg/L) and 3 different seedling explants (cotyledon, hypocotyl and root) was used to callus formation. High-quality callus was observed in eight different of hormone-explant combinations. Successful cell suspension culture was achieved only by using callus created from cotyledon explants treated with 0.1 mg/L 2,4-D and 5 mg/L BAP. Furthermore, the study examined the effects of 2% and 4% Serendipita indica cell wall extract as an elicitor on silymarin production in cell suspension culture at three different inoculation times (24, 48, and 72 h). After 48 h of inoculation with 2% fungal extract, the highest level of silymarin (199 ppm) was observed, which was significantly different from the control (46 ppm). The silymarin content of cells increased over time through elicitation with 4% fungal elicitor, while no similar pattern was observed with 2% fungal extract. Based on the results, the cell wall of S. indica can significantly enhance the amount of SLM in the cell suspension culture of S. marianum.

The aim of this study was to investigate the prebiotic potential of Roman nettle seed mucilage in the growth and survival of Lactobacillus rhamnosus (LGG) as well as changes in different physicochemical, reological and sensory properties of fermented milk compared with inulin (commercial prebiotic) during the storage time. For this purpose, values of 0. 025, 0. 05, 0. 1 and 0. 2% (w/w) of nettle seed mucilage and 0. 5 and 1% (w/w) inulin has been added to the recombined milk and after inoculation of bacteria, changes in acidity, syneresis, viscosity, the number of probiotic bacteria and sensory properties were studied during 21 days. The results showed that the addition of mucilage to fermented milk improved the growth and survival of L. rhamnosus and subsequently increase the acidity of the samples. Furthermore, the addition of mucilage compared with inulin, led to reduction in syneresis of the samples and higher counts of probiotics during storage. Finally, according to physico-chemical, microbiological and organoleptic results, samples containing 0. 1% (w/w) of mucilage were considered as the best sample in this study.